Systems biology analysis of human genomes points to key pathways conferring spina bifida risk

Spina bifida (SB) is a debilitating birth defect caused by multiple gene and environment interactions. Though SB shows non-Mendelian inheritance, genetic factors contribute to an estimated 70% of cases. Nevertheless, identifying human mutations conferring SB risk is challenging due to its relative rarity, genetic heterogeneity, incomplete penetrance, and environmental influences that hamper genome-wide association studies approaches to untargeted discovery. Thus, SB genetic studies may suffer from population substructure and/or selection bias introduced by typical candidate gene searches. We report a population based, ancestry-matched whole-genome sequence analysis of SB genetic predisposition using a systems biology strategy to interrogate 298 case-control subject genomes (149 pairs). Genes that were enriched in likely gene disrupting (LGD), rare protein-coding variants were subjected to machine learning analysis to identify genes in which LGD variants occur with a different frequency in cases versus controls and so discriminate between these groups. Those genes with high discriminatory potential for SB significantly enriched pathways pertaining to carbon metabolism, inflammation, innate immunity, cytoskeletal regulation, and essential transcriptional regulation consistent with their having impact on the pathogenesis of human SB. Additionally, an interrogation of conserved noncoding sequences identified robust variant enrichment in regulatory regions of several transcription factors critical to embryonic development. This genome-wide perspective offers an effective approach to the interrogation of coding and noncoding sequence variant contributions to rare complex genetic disorders.

Novel Positional and Biological Candidate Gene for Grip Strength in Older Adults: The Long Life Family Study

Grip strength is a robust indicator of overall health, is moderately heritable and predicts longevity in older adults. Using genome-wide linkage analysis, we identified a novel locus on chromosome 18p linked to grip strength in 4534 individuals from 582 families (age 70.0 ± 15.8, range 24–110 years; 54% women). DNA sequencing was completed to identify single nucleotide variants (SNVs) in the 3.44 – 4.04 mega-basepair region on chromosome 18p. Using the sequencing data, we performed association analyses between the 7312 SNVs in the region and grip strength in families exhibiting evidence for linkage. Models were adjusted for age, age2, sex, height, field center and population substructure. There were 23 families (263 individuals) that contributed to the linkage peak (cumulative logarithm of the odds [LOD] score = 12.4). Six families (112 individuals) accounted for most of the linkage signal (LOD = 6.4). In these 6 families, we found highly significant associations between SNVs in the Disks Large-associated Protein 1 (DLGAP1) gene and grip strength (lead SNV: β= -0.75kg ± 0.15, p-value= 4.3*10-6). Correcting for the top SNV in DLGAP1 reduces the LOD by 72% in these families. Further, the effect allele frequency is much higher in these 6 families (39.7%) compared with both the NHLBI’s Trans-OMICs for Precision Medicine (23.5%) and 1000Genomes (28.0%) references panels. The DLGAP1 gene plays an important role in post-synaptic density of neurons; thus, it is a novel positional and biological candidate gene for follow-up studies aimed at uncovering genetic determinants of muscle strength.

Novel Positional Candidate Gene for Gait Speed Change in Older Adults: The Long Life Family Study

Gait speed is a heritable, robust predictor of longevity in older adults. Using genome-wide linkage analysis in 2379 individuals from 509 families (64±12 years; 45% men), we identified a locus on chromosome 16p linked to gait speed change over 7±1 years (logarithm of the odds score [LOD]=4.2). Gait speed change was calculated using a two-stage growth curve mixed-model. DNA sequencing was completed to identify single nucleotide variants (SNVs) in the linkage region. Association analyses between the 24039 SNVs in the ~1.6mBP region (3.7-5.3mBP) and gait speed change were performed adjusting for age, age2, sex, height, field center, familial relatedness and population substructure. Eleven families (188 individuals) accounted for most of the linkage signal (LOD=6.06). Associations between SNVs flanking the Mesothelin (MSLN) gene and gait speed change were identified (lead SNV rs56850119: β = -0.5±0.1, p = 6.4*10-7). Thus, MSLN is a potential positional candidate gene for mobility decline with aging.

Influence of Polymorphism on the NFkB1 Gene (rs28362491) on the Susceptibility to Sarcopenia in the Elderly of the Brazilian Amazon

Background: Sarcopenia is a disease characterized by progressive reduction in muscle mass and strength or function. Although it is known that sarcopenia may be associated with environmental factors, studies suggest the identification of genes related to skeletal muscle maintenance that explain the susceptibility to the disease. Objective: To analyze the influence of NFkB1 gene polymorphism on susceptibility to sarcopenia in the elderly. Methods: This is a case-control study, which included 219 elderly people, 74 elderly people with sarcopenia, and 145 without sarcopenia. Samples were analyzed for NFkB1 gene polymorphism (rs28362491), genotyped in PCR, and followed by fragment analysis. To avoid misinterpretation due to population substructure, we applied a previously developed set of 61 informative ancestral markers that were genotyped by multiplex PCR. We used logistic regression to identify differences in genotypic frequencies between elderly people with and without sarcopenia. Results: It was observed that the NFkB1 gene polymorphism presented frequencies of 24%, 50%, and 26% for the genotype DEL/DEL, DEL/INS, and INS/INS, respectively. Furthermore, elderly individuals with the INS/INS genotype had increased chances (p = 0.010; OR:2.943; 95%CI:1.301–6.654) for the development of sarcopenia. Conclusion: The INDEL polymorphism of the NFkB1 gene (rs28362491) may influence the susceptibility to sarcopenia in the elderly in elderly people in the Amazon.

Admixture dynamics in colonial Mexico and the genetic legacy of the Manila Galleon

Mexico has considerable population substructure due to pre-Columbian diversity and subsequent variation in admixture levels from trans-oceanic migrations, primarily from Europe and Africa, but also, to a lesser extent, from Asia. Detailed analyses exploring sub-continental structure remain limited and post-Columbian demographic dynamics within Mexico have not been inferred with genomic data. We analyze the distribution of ancestry tracts to infer the timing and number of pulses of admixture in ten regions across Mexico, observing older admixture timings in the first colonial cities and more recent timings moving outward into southern and southeastern Mexico. We characterize the specific origin of the heterogeneous Native American ancestry in Mexico: a widespread western-central Native Mesoamerican component in northern Aridoamerican states and a central-eastern Nahua contribution in Guerrero (southern Mexico) and Veracruz to its north. Yucatan shows lowland Mayan ancestry, while Sonora exhibits a unique northwestern native Mexican ancestry matching no sampled reference, each consistent with localized indigenous cultures. Finally, in Acapulco, Guerrero a notable proportion of East Asian ancestry was observed, an understudied heritage in Mexico. We identified the source of this ancestry within Southeast Asia--specifically western Indonesian and non-Negrito Filipino--and dated its arrival to approximately thirteen generations ago (1620 CE). This points to a genetic legacy from the 17th century Manila Galleon trade between the colonial Spanish Philippines and the Pacific port of Acapulco in Spanish Mexico. Although this piece of the colonial Spanish trade route from China to Europe appears in historical records, it has been largely ignored as a source of genetic ancestry in Mexico, neglected due to slavery, assimilation as "Indios" and incomplete historical records.

The distribution of mutational effects on fitness in Caenorhabditis elegans inferred from standing genetic variation

The distribution of fitness effects for new mutations is one of the most theoretically important but difficult to estimate properties in population genetics. A crucial challenge to inferring the distribution of fitness effects (DFE) from natural genetic variation is the sensitivity of the site frequency spectrum to factors like population size change, population substructure, genome structure, and non-random mating. Although inference methods aim to control for population size changes, the influence of non-random mating remains incompletely understood, despite being a common feature of many species. We report the distribution of fitness effects estimated from 326 genomes of Caenorhabditis elegans, a nematode roundworm with a high rate of self-fertilization. We evaluate the robustness of DFE inferences using simulated data that mimics the genomic structure and reproductive life history of C. elegans. Our observations demonstrate how the combined influence of self-fertilization, genome structure, and natural selection on linked sites can conspire to compromise estimates of the DFE from extant polymorphisms with existing methods. These factors together tend to bias inferences towards weakly deleterious mutations, making it challenging to have full confidence in the inferred DFE of new mutations as deduced from standing genetic variation in species like C. elegans. Improved methods for inferring the distribution of fitness effects are needed to appropriately handle strong linked selection and selfing. These results highlight the importance of understanding the combined effects of processes that can bias our interpretations of evolution in natural populations.

High Genetic Diversity but Absence of Population Structure in Local Chickens of Sri Lanka Inferred by Microsatellite Markers

Local chicken populations belonging to five villages in two geographically separated provinces of Sri Lanka were analyzed using 20 microsatellite markers to determine the genetic diversity of local chickens. Population genetic parameters were estimated separately for five populations based on geographic locations and for eight populations based on phenotypes, such as naked neck, long legged, crested or crown, frizzle feathered, Giriraj, commercial layer, crossbreds, and non-descript chicken. The analysis revealed that there was a high genetic diversity among local chickens with high number of unique alleles, mean number of alleles per locus (MNA), and total number of alleles per locus per population. A total of 185 microsatellite alleles were detected in 192 samples, indicating a high allelic diversity. The MNA ranged from 8.10 (non-descript village chicken) to 3.50 (Giriraj) among phenotypes and from 7.30 (Tabbowa) to 6.50 (Labunoruwa) among village populations. In phenotypic groups, positive inbreeding coefficient (FIS) values indicated the existence of population substructure with evidence of inbreeding. In commercial layers, a high expected heterozygosity He = 0.640 ± 0.042) and a negative FIS were observed. The positive FIS and high He estimates observed in village populations were due to the heterogeneity of samples, owing to free mating facilitated by communal feeding patterns. Highly admixed nature of phenotypes was explained as a result of rearing many phenotypes by households (58%) and interactions of chickens among neighboring households (53%). A weak substructure was evident due to the mating system, which disregarded the phenotypes. Based on genetic distances, crown chickens had the highest distance to other phenotypes, while the highest similarity was observed between non-descript village chickens and naked neck birds. The finding confirms the genetic wealth conserved within the populations as a result of the breeding system commonly practiced by chicken owners. Thus, the existing local chicken populations should be considered as a harbor of gene pool, which can be readily utilized in developing locally adapted and improved chicken breeds in the future.

Population genetic analysis of 12 X-chromosomal STRs in a Swiss sample

X-chromosomal STRs are a powerful tool to assess a broad variety of complex kinship scenarios. We introduce herewith the first Swiss X-STR dataset based on 1198 individuals (592 female, 606 male), characterized with the Qiagen Investigator® Argus X-12 QS multiplex kit. Anomalous allele patterns, allele and haplotype frequencies, and forensic and population genetic parameters are presented. We detected linkage disequilibrium within three out of the four designated linkage groups and no apparent intra-national population substructure. We compared the dataset to a global panel of X-STR datasets and it fits well in the European context, as expected.

Systems Biology Analysis of Human Genomes Points to Key Pathways Conferring Spina Bifida Risk

Spina bifida (SB) is a debilitating birth defect caused by multiple gene and environment interactions. Though SB shows non-Mendelian inheritance, genetic factors contribute to an estimated 70% of cases. Nevertheless, identifying human mutations conferring SB risk is challenging due to its relative rarity, genetic heterogeneity, incomplete penetrance and environmental influences that hamper GWAS approaches to untargeted discovery. Thus, SB genetic studies may suffer from population substructure and/or selection bias introduced by typical candidate gene searches. We report a population based, ancestry-matched whole-genome sequence analysis of SB genetic predisposition using a systems biology strategy to interrogate 298 case-control subject genomes (149 pairs). Genes that were enriched in likely gene disrupting (LGD), rare protein-coding variants were subjected to machine learning analysis to identify genes in which LGD variants occur with a different frequency in cases vs. controls and so discriminate between these groups. Those genes with high discriminatory potential for SB significantly enriched pathways pertaining to carbon metabolism, inflammation, innate immunity, cytoskeletal regulation and essential transcriptional regulation, indicating their impact on the pathogenesis of human SB. Additionally, interrogation of conserved non-coding sequences identified robust variant enrichment in regulatory regions of several transcription factors critical to embryonic development. This genome-wide perspective offers an effective approach to interrogation of coding and non-coding sequence variant contributions to rare complex genetic disorders.